2017
DOI: 10.1080/19475705.2017.1391883
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Comparing control methods of water inrush disaster using mathematical programming: modelling, analysis and a case study

Abstract: Water inrush from coal floor is one of the main disasters in underground coal mining operations. When establishing or selecting control methods, various factors, such as cost, risk and operability, should be taken into consideration. However, due to the lack of effective mathematical models, the selecting process in practice relies solely on engineering experiences, which may not lead to an optimal and effective decision. This paper proposes a method that considers the parameters, variables, and constraints in… Show more

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Cited by 3 publications
(2 citation statements)
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“…The water control measures used in mining a shallow coal seam may be inadequate for deep-water control. Moreover, the cost and difficulty of constructing such measures increase with depth, and the equilibrium between the groundwater and the eco-system is destroyed [26][27][28][29][30]. Therefore, further in-depth research into methods of preventing and controlling water inrush into mines is needed.…”
Section: Introductionmentioning
confidence: 99%
“…The water control measures used in mining a shallow coal seam may be inadequate for deep-water control. Moreover, the cost and difficulty of constructing such measures increase with depth, and the equilibrium between the groundwater and the eco-system is destroyed [26][27][28][29][30]. Therefore, further in-depth research into methods of preventing and controlling water inrush into mines is needed.…”
Section: Introductionmentioning
confidence: 99%
“…Further, Li et al (2011) performed a numerical investigation of groundwater outbursts near faults in underground coal mines, providing highly meaningful guides for investigating the mechanism and preventing groundwater outbursts induced by faults in practice. Many other methods to evaluate and predict mine water inrush have been developed (Wildemeersch et al 2010;Li CP et al 2013;Li T et al 2013;Shi et al 2014;Wu et al 2016;Bai et al 2016;Qi et al 2017). Most of the methods mentioned are multi-factor comprehensive evaluation methods.…”
Section: Introductionmentioning
confidence: 99%